Method in connection with engine control

ABSTRACT

This invention relates to a method in connection with engine control, wherein a combustion feedback signal is derived by measuring one or more combustion related parameters during a chosen time period of a first combustion cycle, for control of a possible fault, wherein at least one reference feature for said parameters has been determined previously, and comparing said measured combustion feed back signal with said reference feature for automatic adaptation of at least one combustion related variable during a forthcoming combustion cycle wherein at least one reference features for each one of at least two different fault situations having been determined previously, and that a diagnosis  3  of said first combustion cycle is performed on the basis of said combustion feedback signal being processed and compared (T 1 -T n ) with each one of said reference features, the result of which is analysed by a decision logic, whereafter a diagnosis (D) is established by means of which one or more variables in a forthcoming combustion cycle is/are regulated in dependence of the outcome (D) of said diagnosis, thereby achieving fault tolerant engine control.

TECHNICAL FIELD

The present invention relates to a novel method in connection with afault tolerant engine control system, wherein a combustion feedbacksignal is derived by measuring, in a combustion chamber, one or morecombustion related parameters during a chosen time period of a firstcombustion cycle. For the corresponding time period, an ideal referencesignal for said parameters has been previously determined. The method isprimarily intended for control of Otto engines or Diesel engines.

BACKGROUND OF THE INVENTION

In engine control, it is a challenge to keep engine efficiency andcombustion stability as high as possible while minimising emissions.

Control of Otto engines basically amounts to controlling three primaryvariables: ignition timing and fuel and air injected into the cylinder.For the two latter both the mass and the timing are important and theseare controlled separately using different actuators such as thethrottle, the fuel injectors, and the intake valves depending on enginedesign and mode of operation. For Diesel engines the main controlvariables are timing and mass of injected fuel. The main actuators fordiesel engine control are, consequently, the fuel injectors. In today'sengine control systems, most of the control functionality is implementedin form of look-up tables, which give the optimal ignition timing, say,for a certain operating point of the engine and at certain prevailingambient condition. These systems require extensive calibration tests tomeet the performance requirements under all driving conditions,including varying speed and load, fuel quality, air temperature, airpressure, air humidity, etc. Calibration of an engine management systemis therefore typically a very time consuming and expensive task andaccordingly there is a need for other control possibilities, especiallysince the requirements are continuously augmented.

It has been suggested to use continuous measurements of combustionconditions (combustion feedback signal) in order to eliminate the needof extensive calibration. However, known systems which use continuousmeasurements for engine control all show some drawbacks, as will beexplained later. Ionisation current measurements and in-cylinderpressure measurements are two possible ways of obtaining desiredinformation (combustion feedback signal) for engine control, as is knownfrom e.g. SE-504197. The combustion feedback signal can be measuredeither directly in the combustion chamber, (as is known per se from e.g.R. Müller, M. Hart, A. Truscott, A. Noble, G. Krötz, M Eickhoff, C.Cavalloni, and M. Gnielka, “Combustion Pressure Based Engine ManagementSystem”, SAE paper no. 2000-01-0928, 2000; J. Auzins, H. Johansson, andJ Nytomt, “Ion-gap sense in misfire detection, knock and enginecontrol”, SAE paper no. 950004, 1995) or indirectly using non-intrusivesensors (as is known per se from, e.g. M. Schmidt, F. Kimmich, H.Straky, and R. Isermann, “Combustion Supervision by Evaluating theCrankshaft Speed and Acceleration”, SAE paper no. 2000-01-0558, 2000; M.Sellnau, F. Matekunas, P. Battiston, C.-F. Chang, and D. Lancaster,“Cylinder-Pressure-Based Engine Control Using Pressure-Ratio-Managementand Low-Cost Non-Intrusive Cylinder Pressure Sensors”, SAE paper no.2000-01-0932, 2000). As described in said publications (and publicationsdefined below) these measurements are used for closed-loop enginecontrol and that primary benefits of such closed-loop engine control arelower fuel consumption and emissions. Secondary benefits are variouspossible improvements in terms of improved misfire and knock detection,individual cylinder air/fuel ratio control, camshaft phasing, control ofstart-of-combustion, EGR rate control, etc. See e.g. Muller et al.(2000); Sellnau et al. (2000) according to the above, or H. Wilstermann,A. Greiner, P Hohner, R. Kemmler, R. Maly, and J. Schenk, “IgnitionSystem Integrated AC Ion Current Sensing for Robust and Reliable OnlineEngine Control”, SAE paper no. 2000-01-0553, 2000; or L. Nielsen and L.Eriksson, “An Ion-Sense Engine Fine-Tuner”, IEEE Control Systems, 1998.

However, these known engine control systems all have in common that theyare not fault tolerant, i.e. it may control/change the wrong variablesince the interrelation between the different variables may be verycomplex and therefore extremely difficult to handle in both open-loopand closed-loop control systems. If for instance the fuel/air mixture isnot optimised this may lead to a changed burn rate which in turn leadsto a change in the peak pressure position that is used for closed-loopignition timing control (e.g. SE 504 197). This leads to asuboptimisation of the engine control, which results in decreasedefficiency of the engine and higher emission levels. There is also arisk that a multiple loop control system may cause drastic interferenceproblems. Moreover they require time consuming tuning. The inventionalleviates all these problems.

SHORT DESCRIPTION OF THE INVENTION

It is an object of the present invention to present a fault tolerantengine control system by utilising combustion feedback information,which is achieved by a method according to the invention, as presentedin claim 1.

The proposed system leads to improved performance and increasedfunctionality compared to existing solutions for engine control, and isconceptually simpler and therefore also more cost efficient.

According to a further aspect of the invention model-based diagnosis isused. By using model-based diagnosis, preferably parametric, a uniquehighly efficient diagnosis system can be designed and quantitativeinformation about the size of the fault be obtained, which enablesefficient adaptation of the control law, for optimisation of theperformance of an engine.

Parametric modelling of the ionisation current signal is indeed knownper see from, e.g. SE 504 197, which suggests determining the timelocation of the pressure peak during a combustion cycle, by detectingthe ionisation degree in the combustion chamber and fitting a parametricmodel to the measured ionisation current. A peak point in the modelcurve is used in order to determine the time location of the pressurepeak during the combustion cycle. According to a preferred embodiment,the measured ionisation current is parameterised by being fitted to twoconsecutive and partially overlapping Gaussian functions. It is alsosuggested to control the ignition timing of the combustion cycle bycontrolling the pressure peak to lie within a predetermined timeinterval, the location of which depends at least on the prevailing loadand motor speed. In H. Klövmark. “Estimating Air/Fuel Ratio fromGaussian Parameterisations of the Ionisation Currents in InternalCombustion SI Engines”, Master thesis EX 065/1998, Chalmers Universityof Technology, 1998, it has also been suggested to parameterise themeasured ionisation current in order to estimate air/fuel ratio.

However, none of the latter described systems are able of performingfault tolerant engine control and they also only feature single-variableoptimisation, not multivariable optimisation.

The proposed engine control system combines three different techniquesin a unique manner resulting in a fault tolerant engine control system,which may provide an enormous progress in controlling engine efficiency,high combustion stability and minimised emissions.

According to another aspect of the invention, the type of faults thatare detected and which the control system is adapted to handle is one ormore of the fault situations in the group that comprises misfire,pre-ignition, knock intensity, wrong location of peak pressure, wrongair-fuel ratio and wrong EGR rate.

DETAILED DESCRIPTION OF THE INVENTION

In the following, the present invention will be described in moredetail, while referring to the drawing figures, of which:

FIG. 1 is showing an overall structure of a fault tolerant enginecontrol system according to the invention,

FIG. 2 is describing the diagnosis system used in FIG. 1,

FIG. 3 is describing a conceivable method for the diagnosis tests usedin FIG. 2,

FIG. 4 is describing a feedback control system, which may be used forthe engine control according to the invention,

FIGS. 5a-b is showing two examples of ionisation current cycle-to-cyclevariations and average behaviour,

FIGS. 6a-b is showing two examples of fitting results that may beobtained when parameterising the measured signals,

Fault tolerant control aims at designing control systems that cancontinue to operate despite faults or other disturbances that may affectthe process. To achieve fault tolerance one must combine fault diagnosisand control. The basic idea in most fault tolerant control systems is tocontinuously monitor the status of the system and to make suitablechanges in the control strategy to adapt to the new situation, if afault has occurred.

The overall idea of the invention is to estimate a, preferablyparameterised, model of a combustion feedback signal (e.g. a cylinderpressure signal or an ionisation current signal) and to compare thismodel with some reference value(s) for a number of different variables,in order to qualitatively and quantitatively determine a faultsituation. Based on this information, the engine control is adapted toimprove efficiency and combustion stability and to reduce emissions inthe next combustion cycles.

The overall structure of the proposed system is depicted in FIG. 1. Theinputs to the system are the previous actuator signals 1 (if necessary)and the combustion feedback signal 2, e.g. a cylinder pressure curve oran ionisation current curve. These signals are fed into a diagnosissystem 3, which performs a classification of the combustion into one ofthe considered classes: normal combustion, misfire, etc. Theclassification is preferably based on an estimation of a parametricmodel of the combustion feedback signal and can be done directly usingthe estimated parameter values (e.g. Nielsen and Eriksson (1998)according to the above), or indirectly through some additionalprocessing of these values (which, in addition, may require theavailability of the previous actuator signals; e.g. H. Klövmark (1998)according to the above). The output from the diagnosis system is theresult 4 of this classification plus the estimated parameter values 5.Supplied with this information, the engine control unit 6 calculates theoptimal actuator signals 7 for control of the next combustion cycle. Apreferred implementation involves using the diagnosis result 7 in amode-switching scheme for the engine controller, so that the beststrategy (among a number of pre-designed ones) is chosen to improve thecontrol. This may be achieved by providing the control unit 6 with amemory unit comprising a number of pre-programmed controlstrategies/corrections among which a processing unit of the control unitcan chose depending on the diagnosis result D. The parameters 5 are usedto determine the size of the corrections of the actuator signals fromtheir last values.

In the preferred embodiment, the combustion is classified by means ofparametric modelling of the combustion feedback signal, and thisinformation is thereafter used for the diagnosis, i.e. to adapt thecontrol action.

For the description of the diagnosis system 3, FIG. 2, there is adopteda quite general form proposed in M. Nyberg, “Model Based FaultDiagnosis: Methods, Theory, and Automotive Engine Applications”. PhDthesis, Linköping University, 1999, see FIG. 2. As shown in the figure,the process 8 (the combustion) is subject to faults and disturbances 9and it is the diagnosis system's task to diagnose the system's status(type of fault/s) based on observations of the process inputs 1 (=theprevious actuator signals) and outputs 2 (=the combustion feedbacksignal). The primary output of the diagnosis system is the diagnosisstatement D. As a secondary output we will use estimated parametervalues, which can be obtained from the diagnosis system 3.

To facilitate fault isolation, one has to distinguish between severalpossible fault modes. Typically this is done by using a bank ofdiagnosis tests T₁-T_(n) combined with a decision logic 10 thatdetermines which type of fault has occurred, see FIG. 2. The individualtests T₁-T_(n) are often implemented using thresholding, which can beinterpreted as hypothesis testing (Nyberg (1999) according to theabove), as will be described in more detail below in connection withFIG. 3.

In the application of the present invention we are interested indetecting/estimating faults/abnormalities such as

Misfire (T1)

Pre-ignition (T2)

Knock intensity (T3)

Location of peak pressure (T4)

Air-fuel ratio (T5)

EGR rate (T6)

using the combustion feedback signal. In principle, we need to devicedifferent diagnosis tests for each fault mode considered to facilitatefault isolation. Confer FIG. 2. In some cases, though, the number oftests can be reduced by use of a clever decision logic in the diagnosissystem.

FIG. 3 describes how a test T_(i) is typically implemented. For thecomputation of the test quantities R_(i) there is preferably used aunified approach for all tests based on fitting a parametric model tothe measured combustion feedback signal 1. To classify the combustion,the estimated parameter values (the estimated curve shape) arethereafter compared to different reference/“nominal” ones, e.g. one setextreme parameters per considered fault/abnormality mode; according toanother aspect of the invention, one or more extreme signals and/or oneor more ideal reference signals which is/are used for the diagnosisis/are chosen in dependence of the current operating conditions of theengine. Thus, the ideal and extreme signals chosen for the diagnosiscomparison may vary depending on factors such as the currentlyprevailing temperature, the load and the engine speed. Also, the extremesignals may affect each other, whereby e.g. when a knocking situationhas been determined; the entire signal is enhanced in amplitude, in itsturn leading to other extreme signals being altered.

The comparison can for example be made on the basis on the Euclideandistances between the current parameter vector and the nominal ones, oron the basis of single-parameter comparisons. This corresponds to“Calculation of test quantity” R_(i) in FIG. 3. The next step is thethresholding J_(i) followed by the final decision D_(i), which isimplemented by the decision logic, cf. FIG. 2

From a pure controls perspective, the system in FIG. 1 can be redrawn asa standard feedback control system, as shown in FIG. 4. The idea is tocompare the measured output 2 with some reference values 11 and toupdate the input 1 based on the difference between these two. Thecontroller 12 can be static, but most often it is dynamic (i.e. someform of memory); a standard example is PI-control (Proportional andIntegrating control).

If we translate this to the engine application, the feedback 2 isobtained through the measurement of the combustion related parameter.This signal is fed into the diagnosis system 3, which performs ananalysis of the signal and compares the shape of the signal with someideal or reference shape (or rather shapes, since the diagnosis systemcontains a number of such tests in parallel). This comparison results ina classification D of the latest combustion into one of the consideredtypes (normal, misfire, knocking, etc) and in an estimate of theseverity of the fault (abnormality). The classification can be used in amode-switching strategy for the engine controller, so that the correctstrategy is chosen to improve the control. The estimated severity of thefault is used to determine the size of the correction to the inputsignal. This can, for example, be implemented using a PI-controller.

EXAMPLE

To further explain the concept behind the classification and theparameter estimation according to the invention, there is now presentedan example where the ionisation current signal is used as combustionfeedback signal. The ionisation current (and also the cylinder pressure)is directly coupled to the combustion and contains all necessaryinformation on the combustion quality. Hence it is well suited forengine control purposes.

Modelling of Ionisation Current Signals

FIG. 5a-b shows two examples of ionisation current cycle-to-cyclevariations and average behaviour. FIG. 5a shows a single ionisationcurrent curve and FIG. 5b shows a number of consecutive cyclesand—inverted—the average of these curves.

Several studies, e.g. Nielsen and Eriksson (1998) according to theabove, have shown that the ionisation currents can be effectivelymodelled using a parametric radial basis function network. In thisexample there is considered models of the form:

P(θ)=g ₁(θ)+g ₂(θ)g ₁(θ)=α₁ ·e ^(−α) ^(₂) ^((9 −α) ^(₃) ⁾ ² , g ₂(θ)=α₄·e ^(−α) ^(₃) ^((9 −α) ^(₄) ⁾ ²

This gives a model with a total of six parameters, which can be fittedto the measurement data using some numerical estimation routine. Astandard approach would be to consider a least-squares criterion and touse a Gauss-Newton type of search algorithm. Two examples of the type offitting results that are possible to obtain, with the use ofleast-squares fit, are shown in FIG. 6a-b. (The plot shows a particularwindow in the crank angle domain). Note that the parameter α₁, forexample, defines the height of the first basis function g₁ and α₂ and α₃the width and position of it, respectively, in the crank angle domain.Analogous interpretations of the remaining three parameters apply forthe second basis function g₂.

In Nielsen and Eriksson (1998) according to the above it is shown thatthis type of modelling of the ionisation current can be performed inreal time for cycle-to-cycle closed-loop control of the ignition timing.Building on this, the Klövmark (1998) thesis according to the abovestudied various possibilities for estimating the air-fuel ratio usingbasically the approach suggested here: parametric modelling of theionisation current (the combustion feedback signal) followed by air-fuelratio estimation using the estimated parameter values. Supported bythese (and other) studies, the present invention extends this idea toinvolve more engine control functions such as misfire detection andprevention, knock control, individual cylinder air-fuel ratio control,and EGR rate control and to establish a diagnosis based on the combinedresult of possible different identified faults/disturbances. Accordingto a preferred embodiment of the invention these functionalities areimplemented in the unified way described above, using the sameparametric model for different tests, which leads to saved computationsand promises to give improved performance compared to existingtechniques.

In order to give two examples of the modelling of the combustionfeedback signal, misfire detection and knock estimation will be brieflydiscussed in the following.

Misfire Detection

The problem is to detect if a misfire has occurred. A misfire isrecognised by no or very little combustion intensity. Since theionisation current directly reflects the combustion intensity it isclear that the ionisation current signal will vanish or be very smallfor a misfire. Consequently, for a misfire the height and widthparameters α₁, α₂, α₄ and α₅ will be zero (small), which corresponds tothe nominal parameter values in the misfire case. Thus, if it isdetected, after the parameter estimation, that the height and widthparameters of the resulting model are below some suitably chosenreference value threshold, the latest combustion cycle can be recognisedto be a misfire.

Another possibility is to measure combustion intensity by calculatingthe area under the functions over a window in the crank angle domain. Asthis integral can be calculated analytically and stored as a function,which is called when the estimated parameter values has beenestablished, it is possible to detect misfire when thisintegral/function value is below the reference value threshold.

The outlined ideas are just two possibilities for implementing misfiredetection using the proposed approach. Several other variations of thistheme are of course also possible.

Knock Estimation

The pressure variations present in the cylinder during engine knockingcan severely damage the engine; hence it is very important to haveefficient knock detection and control algorithms. The frequency of theknock is fixed (roughly) and engine dependent and knock always occurafter the piston has reached top dead centre (TDC). These facts allowsfor efficient knock estimation through suitable windowing (in the crankangle domain) and band-pass filtering of the cylinder pressure or theionisation current.

In the framework as presented, the parameterised model will typicallynot be able to pick up the (high) frequency components in the combustionfeedback signal due to knock, and hence the resulting model will presenta “knock-free” counterpart of the measured signal. If the differencebetween the measured signal and the (knock-free) model is establishedand the energy (or some other norm/measure) of this signal is computedover a suitably chosen window, it is possible to estimate the knockintensity. A benefit of this approach to knock estimation is that theparametric model, which is estimated anyway for other purposes, can bere-used also for this purpose. Further, the suggested implementationidea also avoids band-pass filtering of the combustion feedback signal,which saves computation.

The fault-tolerant engine control system according to the invention canbe expected to give a level of performance and robustness that isimpossible to achieve with standard approaches, which typically utiliselook-up tables and open-loop control. Thanks to the modular design ofthe system and re-use of the estimated model in several parts (tests)the computational load can also be kept reasonably small. This advantageis expected to become more and more important as the performancerequirements on the engine control systems become higher. A relatedissue is that of calibration or tuning, which today is a very timeconsuming and costly part of engine development. The solution accordingto the invention can alleviate these problems while giving higherperformance. It can also be noted that the system also replaces thespecial diagnosis functions that are used today to detect misfire andknock and promises to improve diagnosis performance as well, compared tothe standard algorithms. This further adds to the advantages that areobtained with the proposed system.

Air/fuel Ratio and Ignition Timing Control

As mentioned above, one of the main features of the invention is theidea to use multivariable optimisation. Consider as an example the caseof air/fuel ratio control and ignition timing control. For optimalcatalyst performance it is important to control the air/fuel ratiotightly around the stochiometric value. For a certain ignition timingthis leads under normal conditions to a particular combustiondevelopment and hence a particular ionisation curve shape. Assumingcontrol of the air/fuel ratio (a/f) within a range (e.g. 0,8<a/f<1,2)near and slightly below the stochiometric value (a/f=1), a more leanmixture (a/f is in the upper part of the range) leads to a slower burnrate and consequently a later peak pressure position. The opposite istrue for a rich mixture, i.e. a/f is in lower part of the range.

In SE 504 197 a method for closed-loop ignition timing control isdescribed. The idea is to locate the peak pressure position (PPP) and toadjust the ignition timing to keep the PPP in a narrow window foroptimal efficiency of the engine.

It is not hard to realise that this ignition timing control strategy mayfail and lead to suboptimisation if the reason why the PPP is moved isnot a change in the ignition timing but rather a change in the air/fuelratio, as exemplified above.

According to another known prior art, example, the air/fuel ratio is,during steady state conditions, normally controlled in a closed loopthrough feed-back from an oxygen sensor in the exhaust. Duringtransients or during the warm up phase the air/fuel ratio is normallycontrolled in an open loop using look up tables. In an engine controlsystem the actual air/fuel ratio can deviate from the desired because ofvarious kinds of disturbances. One example of disturbances is changes inthe air distribution in the intake manifold. This will result in a widerdistribution in air/fuel ratio over cylinders even if the air/fuel ratiofor the sum of the cylinders still corresponds to the desired value.This kind of disturbances is hard to compensate for using a normalclosed loop lambda control system, as normally one oxygen sensor is usedfor a number of cylinders. An other example of disturbances, that willaffect the air/fuel ratio, is the changes in air humidity. Increasedhumidity will for a given fuel quantity result in a leaner mixture.There is today no technique developed that in an efficient waycompensates for disturbances such as the examples described above.

The solution to the above mentioned problems is to use multivariablediagnosis and optimisation as is suggested in the invention, which willgive improved control performance. If efficiently implemented this willalso save development time and tuning costs.

Example of Changes in Air Humidity

If a vehicle equipped with the proposed diagnosis systems enters a foggyarea and the air humidity increases, the system will handle thedisturbance in the following manner. The example refers to FIG. 1 andFIG. 2 with bank of diagnosis tests T1 to T6, Decision logic 10,Diagnosis statement 4 and Engine Control System 6.

Status Before Entering the Foggy Area:

Test Fault/Abnormalities Diag Status T1 Misfire D1 No misfire T2Pre-Ignition D2 No pre-ignition T3 Knock Intensity D3 No knock T4Location of Peak D4 OK Pressure T5 Air-Fuel Ratio D5 OK T6 EGR Rate D6OK

As no fault condition is detected the Decision logic 10 generates aDiagnosis statement 4 to the Engine Control System 6, that theconditions are ok.

Status After Entering the Foggy Area

Test Fault/Abormalities Diag Status T1 Misfire D1 No misfire T2Pre-Ignition D2 No pre-ignition T3 Knock Intensity D3 No knock T4Location of Peak D4 Very late peak pressure Pressure position T5Air-Fuel Ratio D5 Lean mixture T6 EGR Rate D6 OK

As we can see, the increased humidity reslulted in leaner mixture and adelayed peak pressure location. The diagnosis outputs D1 to D6 areanalysed in the Decision logic 10 and a Diagnosis statement 4 will begenerated as an input for control in the Engine Control System 6. As alean mixture also can be the reason for the late combustion the decisionlogic 10 will as a first action generate a Diagnosis statement 4 thatindicates that the mixture is to lean. The Engine Control System 6 willincrease the amaount of fuel in order to correct the fault. Aftercorrection of the air fuel ratio the status could bee as follows.

Status After Correction of Airf/fuel Ratio:

Test Fault/Abnormalities Diag Status T1 Misfire D1 No misfire T2Pre-Ignition D2 No pre-ignition T3 Knock Intensity D3 No knock T4Location of Peak D4 Late peak pressure Pressure position T5 Air-FuelRatio D5 OK T6 EGR Rate D6 OK

As we can see the location of peak pressure is still to late. This meansthat the delayed peak pressure location was not only due to the leanermixture. The Decision logic 10 will now generate the Diagnosis statement4 for Correction of ignition timing only. After correction of ignitiontiming the status should be as the following.

Status After Correction of Air/fuel Ratio and then the Ignition Timing:

Test Fault/Abnormalities Diag Status T1 Misfire D1 No misfire T2Pre-Ignition D2 No pre-ignition T3 Knock Intensity D3 No knock T4Location of Peak D4 OK Pressure T5 Air-Fuel Ratio D5 OK T6 EGR Rate D6OK

The above example is a very simple example of how one disturbance canaffect more than one combustion parameter. By analysing all diagnosticsoutputs the most correct action can be defined. In other cases there canbe much more complex situations where several combustion parameters areaffected and has to be taken into account.

The invention is not limited to the above-described embodiments, but maybe varied within the scope of the claims.

What is claimed is:
 1. Method in connection with engine control, whereina combustion feedback signal (2) is derived by measuring in real time ina combustion chamber one or more combustion related parameters during achosen time period of a first combustion cycle, for control of apossible fault, wherein at least one reference feature for saidparameters has been determined previously, and comparing said measuredcombustion feed back signal with said reference feature for automaticadaptation of at least one combustion related variable during aforthcoming combustion cycle characterised in that at least onereference feature for each one of at least two different faultsituations having been determined previously, and that a diagnosis (3)of said first combustion cycle is performed on the basis of saidcombustion feedback signal being processed and compared (T₁-T_(n)) witheach one of said reference features, the result of which is analysed bya decision logic, where after a diagnosis (D) is established thatdecides which fault is to be prioritized by means of which one or morevariables in a forthcoming combustion cycle is/are regulated independence of the outcome (D) of said diagnosis, thereby achieving faulttolerant engine control.
 2. Method according to claim 1, characterisedin that said combustion feedback signal (2) is modelled, resulting inone or more parameter values which are used to establish a diagnosis ofsaid first combustion cycle.
 3. Method according to claim 2,characterised in that said combustion feedback signal is modelled by aparameterised function, preferably by means of a radial basis functionnetwork.
 4. Method according to claim 3, characterised in that at leastone of said one or more parameters is used for said comparison, saidreference feature having been paramaterised too.
 5. Method according toclaim 2, characterised in that said parameter values from said modellingalso is used to establish the magnitude for the regulation of thevariables that are to be regulated according to the diagnosis D. 6.Method according to claim 1, characterised in that at least threereference features of at least three different fault situations havingbeen determined previously and being compared.
 7. Method according toclaim 1, characterized in that said reference feature comprises at leastone ideal reference signal and at least one extreme reference signal. 8.Method according to claim 1, characterized in that said combustionfeedback signal consists of an ion current signal, measured in thecombustion chamber.
 9. Method according to claim 1, characterized inthat said combustion feedback signal consists of a cylinder pressuresignal.
 10. Method according to claim 1, characterized in that inputactuator signals (1) for said first combustion cycle are used asadditional information for said diagnosis.
 11. Method according to claim1, characterized in that said one or more extreme signals comprises oneor more extreme signals in the group that consists of misfire,pre-ignition, knock intensity, wrong location of peak pressure, wrongair-fuel ratio and wrong EGR rate.
 12. Method according to claim 1,characterized in that said ideal reference signal and/or said one ormore extreme signals for said comparison is/are chosen in dependence ofthe current operating conditions of the engine.
 13. Method according toclaim 1, characterized in that the variable or variables which is/arecontrolled comprises one or more variables in the group that consists ofignition timing, mass of fuel and/or air injected or timing of fueland/or air injected.
 14. Method according to claim 1, characterized inthat said diagnosis (3) comprises thresholding (J_(i)).
 15. Methodaccording to claim 1, characterized in that said one or more variablesin said forthcoming combustion cycle is/are regulated by calculation ofoptimal actuator signals (7) for that combustion arid/or by choice fromtwo or more pre-designed control strategies.
 16. A computer programmeproduct directly loadable into the internal memory of a digitalcomputer, comprising software code portions for performing the method ofclaim 1, when said product is run in a computer.
 17. A computer readablemedium comprising software code portions for performing the method ofclaim 1 when said product is run in a computer.